Mitigation of risks in the validation of the veracity of registrations shared by financial institutions and the analysis process of money laundering evidence

Abstract

One of the most efficient strategies to fight organized crime is follow the money, since money is the soul of any criminal organization and financial institutions are responsible for notifying public authorities whenever they become aware of suspicious operations. These sectors are characterized as gatekeepers, as Brazil adopts a system of compulsory collaboration between the public and private sectors, in which professionals and entities working in sectors most used by criminals to hide resources must notify public authorities whenever they take knowledge of suspicious operations. The banking system has been experiencing a great impact from the growth of mobility and digital convergence, with the growing use of cell phones (smartphones) as banking channels, imposing a new challenge on financial institutions, since "know your customer" refers to a One of the hardest things to do online: Make sure the person on the other end of the network is really who they say they are. However, by enabling the sharing of records between institutions, they pose a new challenge, since these disruptions required a greater complexity of current regulations, since precisely because of their contemporaneity, it increases the difficulty of specifying relational risks, making the mission more difficult creation and application of anti-washing standards. Thus, the hypothesis that drives this study fits: how to mitigate the risk of handling shared data without harming the "Know your customer" process. The present work, in function of its objectives, was conducted as a bibliographic review research of a qualitative nature, seeking to identify the risks and their mitigation, through the creation of a risk matrix and application of the 5W2H method. It is perceived after completion of the studies that institutions must maintain their current control policies, treating third party data as complementary data, without abdicating the care currently in force and adopting additional measures in the treatment of the data necessary to validate its veracity.